Plot Smarttester’s sensor data for the ISEA use-wear project
Ivan Calandra
2025-01-06 15:44:34 CET
1 Goal of the script
This script plots the sensors data from the Smarttester.
Input CSV file file must be located in
“./analysis/derived_data/”.
Plots will be saved in “./analysis/plots/”.
The knit directory for this script is the project directory.
2 Load packages
library(ggplot2)
library(grateful)
library(gridExtra)
library(knitr)
library(R.utils)
library(rmarkdown)
library(tidyverse)
library(viridis)3 Read in Rbin file
ST_file <- list.files(dir_in, pattern = "Smarttester\\.Rbin$", full.names = TRUE)
ST_data <- loadObject(ST_file)
str(ST_data)'data.frame': 114195 obs. of 10 variables:
$ Sample : chr "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" ...
$ File : num 0 0 0 0 0 0 0 0 0 0 ...
$ Bamboo_position : Factor w/ 5 levels "0","-7.5","-15",..: 1 1 1 1 1 1 1 1 1 1 ...
$ Step : int 0 100000 200000 300000 400000 500000 600000 700000 800000 900000 ...
$ StrokeNr : num 1 1 1 1 1 1 2 2 2 2 ...
$ Angle [°] : num 0.000884 -0.016282 -0.589631 -0.811417 -0.699494 ...
$ Depth [mm] : num 10.15 10.15 9.92 9.36 9.23 ...
$ Torque [Nm] : num 1.4 1.6 4.9 5.7 6.3 7 8.2 -3.9 -2.7 -4.2 ...
$ X_position [mm] : num 275 275 279 284 285 ...
$ X_velocity [mm/s]: num 0.00187 9.88465 59.21647 31.58108 0.39584 ... Sample File Bamboo_position Step StrokeNr Angle [°] Depth [mm]
1 ISEA-EX1 0 0 0 1 0.0008842885 10.151439
2 ISEA-EX1 0 0 100000 1 -0.0162818470 10.146061
3 ISEA-EX1 0 0 200000 1 -0.5896308000 9.922504
4 ISEA-EX1 0 0 300000 1 -0.8114173000 9.362462
5 ISEA-EX1 0 0 400000 1 -0.6994940600 9.229558
6 ISEA-EX1 0 0 500000 1 -0.6383826000 9.255678
Torque [Nm] X_position [mm] X_velocity [mm/s]
1 1.4 275.0000 0.001873783
2 1.6 275.1974 9.884645000
3 4.9 279.2093 59.216473000
4 5.7 284.2325 31.581081000
5 6.3 284.9546 0.395838140
6 7.0 284.9808 0.0404695424 Plot
4.1 Define variables
Define dependent (numeric) variables to plot on the Y axis
4.2 Subset and prepare data for plots
For readability, only every 20th stroke will be plotted. The first 50 strokes going along the positive X axis (i.e. odd strokes from 1 to 100) will also be plotted separately.
4.2.1 Every 20th strokes
# Create a sequence of every 20th strokes, including first and before last strokes
# Before last is necessary because of bidirectional strokes:
# the odd strokes go in one X direction, while the even strokes go in the other
stroke_20 <- seq(1, 2000, by = 20) %>%
c(max(ST_data$StrokeNr) - 1)
# Extract data for these strokes
data_every20 <- filter(ST_data, StrokeNr %in% stroke_20) %>%
# Pivot to longer format for facet plots
pivot_longer(all_of(ST_y), names_to = "parameter", values_to = "value") %>%
# Convert to data.frame
as.data.frame()
# Check result
str(data_every20)'data.frame': 24232 obs. of 8 variables:
$ Sample : chr "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" ...
$ File : num 0 0 0 0 0 0 0 0 0 0 ...
$ Bamboo_position: Factor w/ 5 levels "0","-7.5","-15",..: 1 1 1 1 1 1 1 1 1 1 ...
$ Step : int 0 0 0 0 100000 100000 100000 100000 200000 200000 ...
$ StrokeNr : num 1 1 1 1 1 1 1 1 1 1 ...
$ X_position [mm]: num 275 275 275 275 275 ...
$ parameter : chr "X_velocity [mm/s]" "Depth [mm]" "Angle [°]" "Torque [Nm]" ...
$ value : num 1.87e-03 1.02e+01 8.84e-04 1.40 9.88 ... Sample File Bamboo_position Step StrokeNr X_position [mm]
1 ISEA-EX1 0 0 0 1 275.0000
2 ISEA-EX1 0 0 0 1 275.0000
3 ISEA-EX1 0 0 0 1 275.0000
4 ISEA-EX1 0 0 0 1 275.0000
5 ISEA-EX1 0 0 100000 1 275.1974
6 ISEA-EX1 0 0 100000 1 275.1974
parameter value
1 X_velocity [mm/s] 1.873783e-03
2 Depth [mm] 1.015144e+01
3 Angle [°] 8.842885e-04
4 Torque [Nm] 1.400000e+00
5 X_velocity [mm/s] 9.884645e+00
6 Depth [mm] 1.014606e+014.2.2 First 50 positive (odd) strokes
# Extract data for the first 50 odd strokes
data_1to50 <- filter(ST_data, StrokeNr %in% seq(1, 100, 2)) %>%
# Pivot to longer format for facet plots
pivot_longer(all_of(ST_y), names_to = "parameter", values_to = "value") %>%
# Convert to data.frame
as.data.frame()
# Check result
str(data_1to50)'data.frame': 10500 obs. of 8 variables:
$ Sample : chr "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" "ISEA-EX1" ...
$ File : num 0 0 0 0 0 0 0 0 0 0 ...
$ Bamboo_position: Factor w/ 5 levels "0","-7.5","-15",..: 1 1 1 1 1 1 1 1 1 1 ...
$ Step : int 0 0 0 0 100000 100000 100000 100000 200000 200000 ...
$ StrokeNr : num 1 1 1 1 1 1 1 1 1 1 ...
$ X_position [mm]: num 275 275 275 275 275 ...
$ parameter : chr "X_velocity [mm/s]" "Depth [mm]" "Angle [°]" "Torque [Nm]" ...
$ value : num 1.87e-03 1.02e+01 8.84e-04 1.40 9.88 ... Sample File Bamboo_position Step StrokeNr X_position [mm]
1 ISEA-EX1 0 0 0 1 275.0000
2 ISEA-EX1 0 0 0 1 275.0000
3 ISEA-EX1 0 0 0 1 275.0000
4 ISEA-EX1 0 0 0 1 275.0000
5 ISEA-EX1 0 0 100000 1 275.1974
6 ISEA-EX1 0 0 100000 1 275.1974
parameter value
1 X_velocity [mm/s] 1.873783e-03
2 Depth [mm] 1.015144e+01
3 Angle [°] 8.842885e-04
4 Torque [Nm] 1.400000e+00
5 X_velocity [mm/s] 9.884645e+00
6 Depth [mm] 1.014606e+014.3 Prepare receiving lists
Data for the first 400 strokes of sample ISEA-EX3 were not recorded, so the first 50 positive strokes cannot be plotted for that sample.
# Sample IDs
sample_ID <- levels(factor(ST_data$Sample)) %>%
data.frame(Sample = ., SampleNr = .) %>%
mutate(SampleNr = as.numeric(gsub("ISEA-EX", "", SampleNr))) %>%
arrange(SampleNr)
# Create lists to receive the plots
p_every20 <- p_1to50 <- vector(mode = "list", length = nrow(sample_ID))
names(p_every20) <- names(p_1to50) <- sample_ID$Sample
# Delete ISEA-EX3 from p_1to50
p_1to50[["ISEA-EX3"]] <- NULL4.4 Plots
4.4.1 Every 20th stroke
# Plot for every sample
for (i in names(p_every20)) {
# Filter data per sample
data_every20_i <- filter(data_every20, Sample == i)
# Prepare plot
p_every20[[i]] <- ggplot(data = data_every20_i,
aes(x = .data[[X_name]], y = value, color = StrokeNr)) +
# Draw one line per stroke
geom_line(aes(group = StrokeNr), alpha = 0.7, linewidth = 0.4) +
# Facet plot by 'parameter' (= 'ST_y')
facet_wrap(~ parameter, scales = "free_y") +
# The palette 'viridis' is printer- and colorblind-friendly, and perceptually uniform
scale_color_viridis(trans = "reverse") +
# Light theme, and remove x-axis text and ticks
theme_classic() +
# No y-axis label and title from sample_ID$Sample
labs(y = NULL, title = i, x = X_name_leg)
}
# Print list of plots
print(p_every20)$`ISEA-EX1`
$`ISEA-EX2`
$`ISEA-EX3`
$`ISEA-EX4`
$`ISEA-EX5`
$`ISEA-EX6`
$`ISEA-EX7`
$`ISEA-EX8`
$`ISEA-EX9`
$`ISEA-EX10`
$`ISEA-EX11`
$`ISEA-EX12`
4.4.2 First 50 strokes
Data for the first 400 strokes of sample ISEA-EX3 were not recorded, so the first 50 positive strokes cannot be plotted for that sample.
# Plot for every sample
for (i in names(p_1to50)) {
# Filter data per sample
data_1to50_i <- filter(data_1to50, Sample == i)
# Prepare plot
p_1to50[[i]] <- ggplot(data = data_1to50_i,
aes(x = .data[[X_name]], y = value, color = StrokeNr)) +
# Draw one line per stroke
geom_line(aes(group = StrokeNr), alpha = 0.7, linewidth = 0.4) +
# Facet plot by 'parameter' (= 'ST_y')
facet_wrap(~ parameter, scales = "free_y") +
# The palette 'viridis' is printer- and colorblind-friendly, and perceptually uniform
scale_color_viridis(trans = "reverse") +
# Light theme, and remove x-axis text and ticks
theme_classic() +
# No y-axis label and title from sample_ID$Sample
labs(y = NULL, title = i, x = X_name_leg)
}
# Print list of plots
print(p_1to50)$`ISEA-EX1`
$`ISEA-EX2`
$`ISEA-EX4`
$`ISEA-EX5`
$`ISEA-EX6`
$`ISEA-EX7`
$`ISEA-EX8`
$`ISEA-EX9`
$`ISEA-EX10`
$`ISEA-EX11`
$`ISEA-EX12`
# Save list of plots
ggsave(filename = "ISEA_use-wear_Smarttester-plots_50strokes.pdf",
path = dir_plots, width = 190, units = "mm",
plot = marrangeGrob(p_1to50, nrow = 1, ncol = 1, top = NULL))5 sessionInfo()
R version 4.4.2 (2024-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 10 x64 (build 19045)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.utf8
[2] LC_CTYPE=English_United States.utf8
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.utf8
time zone: Europe/Berlin
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] viridis_0.6.5 viridisLite_0.4.2 lubridate_1.9.4 forcats_1.0.0
[5] stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 readr_2.1.5
[9] tidyr_1.3.1 tibble_3.2.1 tidyverse_2.0.0 rmarkdown_2.29
[13] R.utils_2.12.3 R.oo_1.27.0 R.methodsS3_1.8.2 knitr_1.49
[17] gridExtra_2.3 grateful_0.2.10 ggplot2_3.5.1
loaded via a namespace (and not attached):
[1] sass_0.4.9 generics_0.1.3 stringi_1.8.4 hms_1.1.3
[5] digest_0.6.37 magrittr_2.0.3 evaluate_1.0.1 grid_4.4.2
[9] timechange_0.3.0 fastmap_1.2.0 rprojroot_2.0.4 jsonlite_1.8.9
[13] scales_1.3.0 textshaping_0.4.1 jquerylib_0.1.4 cli_3.6.3
[17] rlang_1.1.4 crayon_1.5.3 munsell_0.5.1 withr_3.0.2
[21] cachem_1.1.0 yaml_2.3.10 tools_4.4.2 tzdb_0.4.0
[25] colorspace_2.1-1 vctrs_0.6.5 R6_2.5.1 lifecycle_1.0.4
[29] ragg_1.3.3 pkgconfig_2.0.3 pillar_1.10.0 bslib_0.8.0
[33] gtable_0.3.6 glue_1.8.0 systemfonts_1.1.0 xfun_0.49
[37] tidyselect_1.2.1 rstudioapi_0.17.1 farver_2.1.2 htmltools_0.5.8.1
[41] labeling_0.4.3 compiler_4.4.2 6 Cite R packages used
| Package | Version | Citation |
|---|---|---|
| base | 4.4.2 | R Core Team (2024) |
| grateful | 0.2.10 | Rodriguez-Sanchez and Jackson (2024) |
| gridExtra | 2.3 | Auguie (2017) |
| knitr | 1.49 | Xie (2014); Xie (2015); Xie (2024) |
| R.methodsS3 | 1.8.2 | Bengtsson (2003a) |
| R.oo | 1.27.0 | Bengtsson (2003b) |
| R.utils | 2.12.3 | Bengtsson (2023) |
| rmarkdown | 2.29 | Xie, Allaire, and Grolemund (2018); Xie, Dervieux, and Riederer (2020); Allaire et al. (2024) |
| tidyverse | 2.0.0 | Wickham et al. (2019) |
| viridis | 0.6.5 | Garnier et al. (2024) |
| viridisLite | 0.4.2 | Garnier et al. (2023) |
| RStudio | 2024.9.1.394 | Posit team (2024) |
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